Here, we discuss the properties of our communication protocol. Similar to methods employing Attention mechanism to collect useful information from other agents [1]}, [2]}, [3]}, we allow agents to broadcast their latent state representations from the previous step \(\textbf {z}_{t-1}\) . We also assume that agents can observe actions \(\textbf {a}_{t-1}\)  of others. Tuples \((\textbf {z}_{t-1}, \textbf {a}_{t-1})\)  are then transformed by Communication Block to feature vector \(e^i_t\)  that is used to update the agent's world model and predict next action based on the updated latent state. The schematic representation of the execution phase is in Figure REF .
